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Hydrological modelling of a small watershed using MIKE SHE for irrigation planning
Agricultural Water Management 41 (1999) 149±166
Hydrological modelling of a small watershed using MIKE SHE for irrigation planning R. Singha,*, K. Subramaniana, J.C. Refsgaardb a
Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721 302, India b Danish Hydraulic Institute, Copenhagen, Denmark Accepted 22 December 1998
Abstract The physically based distributed modelling system, MIKE SHE, is used to simulate the hydrological water balance of a small watershed with the objective of developing the irrigation plan. Simulation is first conducted over 109 days, concentrating the attention on the main cropping season, i.e., kharif (Jul±Oct), and the average water balance is calculated. It is observed that in spite of the frequent rainfall in the season, there are phases when the water content in the root zone goes below the allowable deficit. In case irrigation is not supplied during these periods, the yield of the paddy will only be about 70% of the potential yield. To attain the potential yield, the irrigation requirement is calculated as 490 and 340 mm for the upstream and downstream ends of the watershed respectively. Irrigation schedule for the purpose is suggested. Hydrological water balance simulation is further extended to the second cropping season, i.e., rabi (Nov±Feb), over 100-day period. Here, the water stored in the existing tank at the outlet is used for the supplemental irrigation in the season. It is seen that the actual yields obtained are very close to the potential yields of the selected crops. The results overall illustrate the applicability of a comprehensive hydrological modelling system for the management of water resources for agricultural purposes in a watershed. # 1999 Elsevier Science B.V. All rights reserved. Keywords: Crop yield; Irrigation planning; Simulation; Water balance; Watershed modelling
1. Introduction Management of land and water resources for enhancing the agricultural production is of growing concern worldwide and this is especially true for developing countries like India. Since by 2000 AD India needs to meet the growing demand of food, fodder and * Corresponding author. Tel.: +91-3222-55224; fax: +91-3222-55303; e-mail: [email protected] 0378-3774/99/$ ± see front matter # 1999 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 2 2 - 0
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fuel for an expected population of 1000 million with diminishing per capita land availability (from 0.50 ha in 1983 to 0.33 ha in 2000 AD), the Ministry of Agriculture, Government of India has set the guideline that watershed is the most rational unit for planning and implementation of the programmes dealing with agricultural production. Subsequently, watershed management has become the cornerstone of planning and development of land and water resources in the country. The major objective behind the watershed approach is to enhance agriculture production in rainfed areas through efficient use of natural resources, within the natural boundaries of the development area. Hydrological simulation models form the basis of information for decisions regarding the development and management of water and land resources in a watershed. Though many hydrological models have been developed in the past, these are mostly lumped, i.e., they refer to the spatially averaged condition of the entire basin (Crawford and Linsey, 1963; Sittner et al., 1969; Holtan et al., 1975; Sugawara et al., 1984). Furthermore, their parameters have no direct physical meaning and cannot easily be derived from measurable properties of the basin. Thus, their applicability is limited only to gauged watersheds where no significant changes in catchment conditions have occurred. To overcome these limitations, considerable efforts within hydrological research have been directed towards development of distributed physically based catchment models (Beven et al., 1984; Rogers et al., 1985). Such models use parameters related directly to the physical characteristics of the catchment viz. topography, soil, vegetation and geology; and spatial variability in both physical characteristic and meteorological conditions. MIKE SHE (Refsgaard and Storm, 1995), a major development in this direction, is a comprehensive deterministic, distributed and physically based modelling system capable of simulating all major hydrological processes in the land phase of the hydrological cycle. Though it has been widely adopted for catchment studies (Bathurst, 1986a, b; Refsgaard et al., 1992; Jain et al., 1992), its applicability for irrigation planning has remained limited (Lohani et al., 1993; Singh et al., 1997). In the present study (Subramanian, 1997), MIKE SHE is adopted for the hydrological modelling of a small watershed with special emphasis on irrigation planning and the methodology and results are presented here. 2. Methodology 2.1. Description of MIKE SHE MIKE SHE is a distributed physically based modelling system capable of describing the entire land phase of the hydrological cycle over the model area. The model area is discretized by two analogous horizontal-grid square networks for surface and ground water flow components. A vertical column of nodes at each grid representing the unsaturated zone (Fig. 1) links these. A finite difference solution of the partial differential equations, describing the processes of overland and channel flow, unsaturated and saturated flow, interception and evapotranspiration, is used for water movement modelling. Though MIKE SHE is well-documented (Abbott et al., 1986a, b; Refsgaard and Storm, 1995), a brief description of its components is given in the following.
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Fig. 1. Schematic representation of MIKE SHE model structure.
2.1.1. Interception and evapotranspiration component The interception process is modelled by introducing an interception storage, expressed as a function of leaf area index (Jensen, 1983). The actual evapotranspiration is calculated based on the potential evapotranspiration using the Kristensen and Jensen model (Kristensen and Jensen, 1975). The actual evapotranspiration rate, consisting of the sum of actual transpiration and soil evaporation, is further adjusted according to vegetation density and water content in the root zone. Actual transpiration depends on the density of crop green material, described by the leaf area index, LAI, soil moisture content in the root zone and the root density. It is expressed as follows. Eat f1 LAIf2 RDFEp
(1)
where Eat actual transpiration; f1 LAI leaf area index function (Fig. 2(a)); f2 soil moisture function (Fig. 2(b)); RDF root distribution function; and Ep potential evapotranspiration. The soil moisture function, f2 , is mathematically expressed as follows: f ÿ c3 Ep (2) f2 1 ÿ f ÿ w where f volumetric moisture content at field capacity; w volumetric moisture content at wilting point; volumetric moisture content; and c3 empirical parameter, mm/d.
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Fig. 2. Variation of f1(LAI) with leaf area index and parameters c1 and c2, (b) Variation of f2() with potential evapotranspiration for constant c3, (c) Variation of soil evaporation with the soil moisture content in upper layers.
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The soil evaporation takes place only from the upper layers (top four nodes in the model set up) and consists of basic evaporation, Ep f3 , and evaporation from the possible water reserve in the upper layers. It is expressed as follows: Es Ep f3 Ep ÿ Eat ÿ Ep f3 f4 1 ÿ f1 LAI
(3)
where Es soil evaporation; and functions f3 and f4 are expressed as follows: 8 for w ; <0 (4) f3 c2 =w for r w ; : for w ; c2 where r residual soil moisture content; and c2 empirical parameter. 8 < ÿ 0:5 w f for 0:5 w f ; f4 f ÿ 0:5 w f : 0 else
(5)
Fig. 2(c) illustrates the variation of soil evaporation, i.e., Es/Ep, with the soil moisture content in the upper layers. The typical values of empirical parameters c1, c2 and c3 for agricultural crops are recommended as 0.31, 0.15 and 10 mm/d respectively. As evident from the governing equations, leaf area index and root depth need to be specified as a function of time for the actual evapotranspiration calculations. 2.1.2. Overland and channel flow component The overland flow process is simulated in each grid square by solving the twodimensional diffusive wave approximation of the Saint±Venant equations. For stream network channel flow, the one-dimensional form of the equation is solved in a separate node system located along boundaries of the grid squares. 2.1.3. Unsaturated zone component Soil moisture distribution in the unsaturated zone is calculated by solving the onedimensional Richards' equation. Extraction of moisture for transpiration and soil evaporation is introduced via sink terms at the node points in the root zone. Infiltration rates are found by the upper boundary that may be either flux controlled or head controlled. The lowest node point included in the finite difference scheme depends on the phreatic surface level, and allowance is made for the unsaturated zone to disappear in cases where the phreatic surface rises to the ground surface. 2.1.4. Saturated zone component The ground water flow is modelled using an implicit finite difference solution of the two-dimensional non-linear Boussinesq equation for an unconfined aquifer. The interaction between the streamflow and groundwater system is calculated on the basis of water levels in the river system and the groundwater table. 2.2. Study area and data availability The watershed under study is located in the western part of the Midnapore district of West Bengal, India between 208200 and 228230 N latitude and 87890 and 878110 E
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Fig. 3. Topographic map of the watershed.
longitude, and forms a part of the 66-B catchment of the Kangsabati river. The geographical area of the watershed is 694 ha. The climate is tropical sub-humid, with average annual rainfall of 1400 mm, 90% of which occurs during the Southwest monsoon (Jun±Oct). The area is primarily rainfed, though a small tank of 170 000 m3 capacity exists for supplemental irrigation. Paddy is the main crop grown in the area. Data on various aspects of the watershed viz. topography, geology, soils, crops, groundwater and meteorology are obtained from the Soil Conservation Department, Government of West Bengal and processed. Fig. 3 presents the topographic map of the area. As evident, the area is slightly undulating with elevation difference of about 30 m between the highest point on the ridge and the outlet. It is also seen that the elevation is decreasing towards the centre of the watershed from both sides of the boundary, along the length of the watershed. This directs the runoff water towards the centre of the watershed first and then to the outlet. Fig. 4 shows the land use patterns of the area. The central part of the area is cultivated land where the elevations are comparatively less. There are a few patches of fallow land. The major proportion of the watershed is under forest. Fig. 5 shows the soil type distribution map of the watershed. There are eight types of soil present in the area, ranging from slow to rapid draining. However, medium draining soils cover most of the cultivated area. Table 1 presents the experimentally determined pertinent physical characteristics of the soils in the area. Fig. 6 shows the stream network having a 4th order main stream. The main stream discharges into a storage tank constructed at the outlet. The water stored in the storage tank is pumped and used for the supplemental irrigation through a network of field channels. To model the inflow into the storage tank, a point neat the outlet is selected for storing the stream flow data during the simulation.
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Fig. 4. Land use pattern map of the watershed.
The major crops are paddy during kharif season (Jul±Oct) and wheat, gram and mustard during the rabi season (Nov±Feb). The crop characteristics like potential yield, leaf area index and root depth are obtained from government experimental farm.
Fig. 5. Soil distribution map of the watershed.
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Table 1 Pertinent physical properties of soils Drainability
Soil name
Bulk density (g/cc)
Saturated hydraulic conductivity (m/s)
Slow
Rg5A1 IIs-top Rg5A1 IIs-bot Hc5A1 IIs-top Fe5A1 IIs Mc5A1 IIs Hc5A1 IIs-bot Mb5B1 IIs Sb1B3 VIIs Sb3B2 IIIs Sb1B3 VIIIs
1.62 1.55 1.60 1.58 1.53 1.65 1.48 1.36 1.50 1.61
3.23 10ÿ7 8.90 10ÿ7 2.03 10ÿ7 1.30 10ÿ7 1.53 10ÿ6 2.98 10ÿ6 3.10 10ÿ6 2.14 10ÿ6 8.90 10ÿ6 1.07 10ÿ5
Medium
Rapid
2.3. Model simulations For running the simulation a grid size of 50 m 50 m is used with automatic classification. Daily simulations are first carried out for the main cropping season, i.e., kharif, over 109 days (Jul 7±Oct 21, 1993). The results are analysed and after assessing the availability of water for the subsequent dry rabi season, the simulations are further extended over 101 days (Nov 4, 1993±Feb, 12, 1994). 3. Results and discussion 3.1. Kharif season 3.1.1. Water balance of the watershed Table 2 presents the weekly-accumulated average water balance of the watershed. It gives the water flow and storage and also the water balance error in the calculation. The total accumulated precipitation during the simulation period is 1334 mm, the daily distribution of which is presented along with the pan evaporation in Fig. 7. The accumulated actual evapotranspiration, including the soil evaporation, is 1184 mm of water, whereas the deficit in the unsaturated zone varies from ÿ295 to ÿ441 mm (a change of ÿ246 mm). The accumulated average value of water stored on the ground surface is 39 mm. An accumulated water balance error of ÿ45 mm (around 4% of the accumulated precipitation) is also observed. 3.1.2. Infiltration to the paddy fields The accumulated infiltration to the paddy field is 628 mm for the greater proportion of the area. However, it is slightly less for the slow draining soil at the downstream side of the watershed. Fig. 8 shows the variation of infiltration to the paddy fields. At the beginning of the season the infiltration rate is comparatively high due to frequent rainfall events.
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Fig. 6. Stream network in the watershed.
3.1.3. Water content at each node of the soil column Fig. 9 shows the water content at each node of the soil column. In spite of the frequent rainfall there are phases when the moisture content in the root zone falls below the allowable deficit (field capacity in case of paddy). This shows that irrigation is needed to meet the crop water demand and to help crop attain its potential yield.
Table 2 Weekly-average accumulated water balance for the kharif season yy-mm-dda 93-7-7 93-7-14 93-7-21 93-7-28 93-8-4 93-8-11 93-8-18 93-8-25 93-9-1 93-9-8 93-9-15 93-9-22 93-9-29 93-10-6 93-10-13 93-10-20 93-10-21
ac.p.b 0 36 137 238 282 282 687 758 820 927 1142 1160 1263 1315 1317 1333 1334
ac.ep.c 0 40 147 251 279 279 627 728 784 805 1071 1092 1113 1137 1160 1181 1184
h-ovld 13 21 29 34 36 36 37 38 38 38 38 38 39 38 39 39 39
q-rive 0 12 23 32 43 43 65 75 86 97 107 119 129 140 151 162 164
thuzf
qszbg
qocbh
ÿ295 ÿ329 ÿ362 ÿ389 ÿ392 ÿ392 ÿ370 ÿ417 ÿ430 ÿ360 ÿ430 ÿ449 ÿ385 ÿ375 ÿ415 ÿ437 ÿ441
0 5 9 12 15 15 19 21 24 26 28 31 33 35 38 41 42
0 1 3 4 5 5 7 8 9 10 11 13 14 16 18 20 20
a
Output year, month and day. Accumulated precipitation. c Accumulated actual evapotranspiration. d Water stored on the ground surface. e Accumulated river outflow. f Deficit in the unsaturated zone. g Net outflow from the top layer of the saturated zone. h Net outflow from overland flow across the catchment boundaries. i Water balance error. b
Fig. 7. Rainfall and evaporation data.
wbleri 0 ÿ3 ÿ6 ÿ11 ÿ14 ÿ14 ÿ20 ÿ24 ÿ26 ÿ29 ÿ34 ÿ34 ÿ38 ÿ42 ÿ43 ÿ45 ÿ45
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Fig. 8. Infiltration to the paddy fields.
3.1.4. Calibration of the model The model is calibrated in three stages. Firstly, by matching the hydraulic conductivitymoisture content relationships derived by the MIKE SHE, based on the soil moisture retention characteristics, saturated hydraulic conductivity, residual moisture content and exponent, and the experimentally determined k± relationships. This is because the previous experience (Singh et al., 1997) has shown the sensitivity of the modelling system to the soil properties. Secondly, the pre- and post-monsoon groundwater table levels, actual and model derived, are matched over the watershed. Here, to match the premonsoon water table level, a separate simulation is run over 36 days (Jun 1±Jul 6). Once
Fig. 9. Water content of an upstream node during kharif season.
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Fig. 10. Comparison of measured and simulated stream flow data.
the desired water table is attained the output file of this simulation is used to provide the initial conditions for the main simulation (hot-start in MIKE SHE terminology). This simulation also helps in calibrating the hydrological properties of the subsurface strata, i.e., horizontal and vertical hydraulic conductivity, specific yield and storage coefficient. Lastly, the simulated daily stream flow is compared with the measured stream flow at the outlet of the watershed for a period of 21 days (Aug 11±Aug 31). Fig. 10 presents the plot of simulated and measured flow over the period. The visual comparison shows that the model performs satisfactorily. However, to evaluate the model performance statistically, two goodness-of-fit criteria, recommended by the ASCE Task Committee (The ASCE Task Committee on Definition of Criteria for Evaluation of Watershed Models, 1993) for evaluating the watershed models, are used. These are the deviation of the flow volumes, Dv, and Nash±Sutcliffe coefficient, R2, and are described below. The first criterion, Dv, complements the visual inspection of the continuous flow record and should be small for model to be acceptable (Dv equals zero for a perfect model). It is mathematically expressed as Dv %
V ÿ V0 100 V
(6)
where V measured flow volume; and V 0 simulated flow volume. The second criterion, R2, is a measure of how well the daily simulated and measured flows correspond and can vary from 0 to 1 (1 indicating a perfect fit). It is mathematically expressed as Pn Qi ÿ Q0i 2 2 (7) R 1 ÿ Pi1 n 2 i1 Qi ÿ Q where Qi measured daily discharge; Qi0 simulated daily discharge; Q average measured discharge; and n number of daily discharge values.
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The values of Dv and R2 for the data set presented in Fig. 10 are found to be 5.7% and 0.68 respectively. This shows that the model performance is satisfactory for the watershed. In addition to these criteria, Student's t-test is also applied to test the difference of means of measured and simulated data. The means of the measured and simulated data are 0.232 and 0.219 m3/s with standard deviations of 0.082 and 0.073 respectively. The calculated value of variable T is 0.53, which is well within the table value, i.e., 2.70, at 1% level of significance. Hence, there is no significant difference between the means of measured and simulated data. This further enforces the conclusion that the model performance is acceptable for the watershed. 3.1.5. Evaluation of the paddy yield The actual yield of the paddy is calculated from the FAO relationship (Doorenbos and Kassam, 1979), modified by replacing evapotranspiration terms with transpiration. The modified relationship is as follows. X n Ya Eat i Ky 1 ÿ (8) 1ÿ Ym Emt i1 where, Ya, Ym actual and maximum attainable yields; Eat actual transpiration; Emt maximum transpiration that would have occurred if there had been no water stress; Ky yield response factor; and i crop growth stage. Eq. (8) performs better than the original FAO relationship when used with the Kristensen and Jensen model (Jorgensen, 1995). Eat and Emt in Eq. (8) are estimated by deducting the soil evaporation from the actual and maximum evapotranspiration values, where the soil evaporation and actual evapotranspiration are estimated using Kristensen and Jensen model. The yield response factor, Ky, is determined from literature (Doorenbos and Kassam, 1979). Using Eq. (8), the actual paddy yield is estimated for periods where soil moisture deficit occurs. It is found that in case irrigation is not supplied the paddy yield will be around 70% of the maximum attainable yield. This shows that the prospects of increasing yield by providing irrigation are high. 3.1.6. Irrigation water requirement of the area To avoid reduction in the paddy yield, the irrigation water requirements (to bring the soil moisture content to the field capacity during the dry phases) are calculated and found to be comparatively higher for the upstream side of the watershed. The total irrigation requirements are 490 and 340 mm for the upstream and downstream sides of the watershed respectively. Fig. 11 presents the amount of water required and the suggested days of applications for the upstream end of the watershed. 3.1.7. Tank storage The water available for storage in the tank is calculated by deducting the total irrigation requirement from the total inflow to the tank for the corresponding month. During July to October, this is found as ÿ48 000, 118 900, 927 000, 233 400 m3 respectively. The negative sign indicates that the monthly irrigation requirement in July exceeds the monthly river inflow. However, this deficit can be met with the existing storage (before simulation) in the tank. The net inflow to the tank at the end of simulation period is
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Fig. 11. Irrigation water requirement for paddy.
estimated as 445 000 m3 though the existing tank capacity is 170 000 m3 only. This shows that the tank capacity can be increased further. This also shows that at the end of the kharif season 170 000 m3 of water remains available for meeting the irrigation water requirement of crops in the subsequent dry rabi season. 3.2. Rabi season 3.2.1. Irrigation for rabi crops The 170 000 m3 of water stored in the outlet tank is considered for irrigating the rabi crops, i.e., wheat, mustard and gram. Consequently, the depth of water available for irrigation is calculated as 54 mm, assuming an overall irrigation efficiency of 70% (Interim Report, 1982). Since the available water is not sufficient to meet the crop water demand, protective irrigation is provided during the critical crop growth periods. Fig. 12 presents the amount and distribution of the protective irrigation for the selected crops. Further, to reduce the computation requirements, field channels are not included in the model setup. The irrigation amount, instead, is modelled as the rainfall.
Fig. 12. Amount and distribution of irrigation water for rabi crops.
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Table 3 Weekly-average accumulated water balance for rabi season yy-mm-dda
ac.pb
93-11-4 93-11-11 93-11-18 93-11-25 93-12-2 93-12-9 93-12-16 93-12-23 93-12-30 94-1-6 94-1-13 94-1-20 94-1-27 94-2-3 94-2-10 94-2-12
0 3 3 3 3 6 10 11 12 14 18 35 82 82 82 82
ac.ep.c 0 14 28 44 59 73 86 98 111 124 136 147 165 181 192 195
h-ovld
q-rive
1 3 5 7 9 11 13 15 17 18 20 21 23 25 26 27
0 4 7 11 14 16 19 21 23 25 27 29 31 33 34 35
thuz6 ÿ468 ÿ486 ÿ507 ÿ530 ÿ551 ÿ568 ÿ584 ÿ600 ÿ617 ÿ633 ÿ645 ÿ644 ÿ619 ÿ639 ÿ654 ÿ659
qszb7
qocb8
wbler9
0 1 1 2 3 4 4 5 6 6 7 7 8 9 9 10
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 ÿ1 ÿ1 ÿ2 ÿ3 ÿ3 ÿ4 ÿ4 ÿ5 ÿ6 ÿ5 ÿ6 ÿ6 ÿ7 ÿ7 ÿ7
a
Output year, month and day. Accumulated precipitation. c Accumulated actual evapotranspiration. d Water stored on the ground surface. e Accumulated river outflow. f Deficit in the unsaturated zone. g Net outflow from the top layer of the saturated zone. h Net outflow from overland flow across the catchment boundaries. i Water balance error. b
3.2.2. Water balance of the watershed Table 3 shows the average weekly water balance of the watershed for the rabi season. Here, the actual evapotranspiration is 195 mm against the total precipitation of 82 mm which includes actual rainfall and total irrigation simulated as rainfall. Also, the deficit in the unsaturated zone varies from ÿ468 to ÿ654 mm (a change of ÿ186 mm). This shows that the soil water stored in the root zone mostly meets the crop water demand. The result here is in tune with the existing conditions in the field where the rabi crops are grown with bare minimum irrigation. 3.2.3. Water content at each node of soil column Fig. 13 shows the representative soil moisture distribution pattern in the root zone for different crops. It is seen that in all cases the moisture content remains well within the readily available moisture content limit during the entire cropping period. For this analysis, a maximum allowable depletion (MAD) value of 0.5 is considered (Stegman, 1983). This shows that the supplemental irrigation provided during critical periods of the crops helps in maintaining the soil moisture status within the desirable limit, in spite of negligible rainfall during the season.
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Fig. 13. Water content for representative nodes during rabi season.
3.2.4. Yield evaluation Using the modified FAO relationship in Eq. (1), the actual yields for the three crops are calculated. It is found that the actual yields are very close to the maximum attainable yields. This shows the importance of supplemental irrigation in the rabi season. Here, it may be noted that the modelling system offers a flexibility to users to change the irrigation schedule in this season, if the actual yield calculations are not favourable. However, since the actual yield values are favourable, the same is not attempted here. 4. Discussion MIKE SHE, a comprehensive physically based distributed modelling system is adopted here for irrigation planning of a small watershed. The modelling system though provides
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the users with a chance to utilise large amount of parametric and input data, its application is not necessarily restricted due to unavailability of some of the data. This is because the model set up can be simplified according to the users' conceptualization of the natural system and the data availability. MIKE SHE, therefore, provides greater flexibility as compared to many simpler models when describing a natural system (Refsgaard and Storm, 1995). Concerning irrigation, MIKE SHE is primarily proposed here as a planning tool and not as a real-time scheduling tool. The major problem faced in rainfed agriculture is the unavailability of irrigation water for the non-rainy cropping season (rabi). This is either due to lack of facilities to store excess water in the rainy season or due to poor management of stored water, over-irrigation in the kharif season often being the culprit. The watershed under study falls in the later category. The application of MIKE SHE in carrying out the detailed hydrological water balance study plays an important role in evaluating the irrigation demands in the kharif season and in deciding the magnitude of water that can be stored for irrigation in the subsequent dry season. This consequently facilitates irrigation and encourages the farmers to cultivate the second crop that is often ignored otherwise. It may, however, be noticed that the advantages of the modelling system cannot be quantified in terms of total production or yield. This is because the crop yield depends on several inputs whereas the analysis here involves only the water production function. Nevertheless, from a qualitative assessment the results appear to provide a reasonable representation of the field conditions in the watershed. 5. Conclusions The hydrological water balance of a small rainfed watershed is simulated using MIKE SHE. Simulation results show that in spite of frequent rainfall during the kharif season, supplemental irrigation is essential for paddy to obtain the potential yield. Based on the water balance analysis, an irrigation schedule for paddy is suggested. Further, the inflow to the outlet tank is analysed and the irrigation water available for the subsequent dry cropping season is estimated. An irrigation plan is then suggested for protective irrigation during the season. Simulation results for the season show that with the proper planning it is possible to meet the irrigation demand of the crops. The study, thus, illustrates the applicability of the comprehensive hydrological modelling system for planning and analysing the irrigation water requirements of crops, based on water balance analyses. Acknowledgements This research was funded by the Indian Council of Agricultural Research, Government of India through a sponsored project. The assistance of Mr. I. Banerjee, B.Tech. student at I.I.T., Kharagpur, in detailed calibration of the model is duly acknowledged. The help rendered by the Watershed officials in data collection is also acknowledged. The authors are grateful to the two referees for their thoughtful criticism and suggestions.
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References Abott, M.B., Bathrust, J.C., Cunge, J.A., O'Connell, P.E., Rasmussen, J., 1986a. An introduction to Europeen hydrological system ± systeme hydrologique Europeen (SHE) Part 1. History and philosophy of physically based distributed modeling system. J. Hydrol. 87, 45±59. Abbott, M.B., Bathrust, J.C., Cunge, J.A., O'Connell, P.E. and Rasmussen, J. 1986b. An introduction to Europeen hydrological system ± systeme hydrologique Europeen (SHE) Part 2. Structure of a physically based distributed modeling system. J. Hydrol. 87, 61±77. Bathurst, J.C., 1986a. Physically based distributed modelling of an upland catchment using the Systeme Hydrologique Europeen. J. Hydrol. 87, 79±102. Bathurst, J.C., 1986b. Sensitivity analysis of the Systeme Hydrologique Europeen for an upland catchment. J. Hydrol. 87, 103±121. Beven, K.T., Kirkby, M.J., Schofield, N., Tagg, A.F., 1984. Testing a physically based flood forecasting model (TOPMODEL) for three UK catchments. J. Hydrol. 69, 119±143. Crawford, N.H., Linsey, R., 1963. A conceptual model of the hydrologic cycle. International Association of Scientific Hydrology Publication No. 63, 573±587. Doorenbos, J., Kassam, A.H., 1979. Yield response to water. Irrig. and Drain. Paper No. 33, Food and Agric. Organization, Rome, Italy. Holtan, H.N., Stiltner, G.F., Hensen, W.H., Lopez, N.C., 1975. USDA-74 revised model of watershed hydrology. Technical Bulletin No. 1518, Agricultural Research Service, U.S. Department of Agriculture, Washington, DC. Interim Report, 1982. National Council on the use of plastics in agriculture. Ministry of Petroleum and Chemicals, Government of India. Jain, S.K., Storm, B., Refsgaard, J.C., Singh, R.D., 1992. Application of the SHE to catchments in India ± Part 2. Field experiments and simulation studies on Kolar sub-catchment of Narmada River. J. Hydrol. 140, 25±47. Jensen, K.H., 1983. Simulation of water flow in the unsaturated zone including the root zone. Technical Series Paper No. 33, Institute of Hydrodynamics and Hydraulic Engineering, Technical University of Denmark, Copenhagen, Denmark. Jorgensen, G.H., 1995. Crop Growth Module ± User Manual. Danish Hydraulic Institute, Copenhagen, Denmark. Kristensen, K.J., Jensen, S.E., 1975. A model of estimating actual evapotranspiration from potential evapotranspiration. Nordic Hydrol. 6, 170±188. Lohani, V.K., Refsgaard, J.C., Clausen, T., Erlich, M., Storm, B., 1993. Applications of the SHE for irrigation command area studies in India. J. Irrig. Drain. Engrg., ASCE 119, 34±49. Refsgaard, J.C., Seth, S.M., Bathurst, J.C., Erlich, M., Jorgensen, B., 1992. Application of SHE to catchment in India Part II: general results. J. Hydrol. 140, 23±59. Refsgaard, J.C., Storm, B., 1995. MIKE SHE. In: Singh, V.P. (Ed.), Computer Models of Watershed Hydrology. Water Resource Publications, CO, USA, pp. 806±846. Rogers, C.C.M., Beven, K.J., Morris, E.M., Anderson, M.G., 1985. Sensitivity analysis, calibration and predictive uncertainty of the institute of hydrology distributed model. J. Hydrol. 81, 179±191. Singh, R., Refsgaard, J.C., Yde, L., Jorgensen, G.H., Thorsen, M., 1997. Hydraulic-hydrological simulations of canal-command for irrigation water management. Irrig. Drain. Sys. 11, 185±213. Sittner, W.T., Schanss, C.E., Monro, J.C., 1969. Continuos hydrograph synthesis with an API-type hydrologic model. Water Resour. Res. 5, 1007±1022. Stegman, E.C., 1983. Irrigation scheduling: applied timing criteria. In: D. Hillel (Ed.), Advances in Irrigation, Vol. 2. Academic Press, New York, USA, pp. 1±30. Subramanian, K., 1997. Hydrological modelling of a watershed using MIKE SHE. M. Tech Thesis, Indian Institute of Technology, Kharagpur, 51 pp. Sugawara, M., Watanabe, E.O., Katsuyana, Y., 1984. Tank model with snow component. Research notes of National Research Centre for Disaster Prevention No. 65, Science and Technology Agency, Japan. The ASCE Task Committee on Definition of Criteria for Evaluation of Watershed Models, 1993. Criteria for evaluation of watershed models. J. Irrig. Drain. Eng., ASCE, 119, pp. 429±442.
Hydrological modelling of a small watershed using MIKE SHE for irrigation planning R. Singha,*, K. Subramaniana, J.C. Refsgaardb a
Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721 302, India b Danish Hydraulic Institute, Copenhagen, Denmark Accepted 22 December 1998
Abstract The physically based distributed modelling system, MIKE SHE, is used to simulate the hydrological water balance of a small watershed with the objective of developing the irrigation plan. Simulation is first conducted over 109 days, concentrating the attention on the main cropping season, i.e., kharif (Jul±Oct), and the average water balance is calculated. It is observed that in spite of the frequent rainfall in the season, there are phases when the water content in the root zone goes below the allowable deficit. In case irrigation is not supplied during these periods, the yield of the paddy will only be about 70% of the potential yield. To attain the potential yield, the irrigation requirement is calculated as 490 and 340 mm for the upstream and downstream ends of the watershed respectively. Irrigation schedule for the purpose is suggested. Hydrological water balance simulation is further extended to the second cropping season, i.e., rabi (Nov±Feb), over 100-day period. Here, the water stored in the existing tank at the outlet is used for the supplemental irrigation in the season. It is seen that the actual yields obtained are very close to the potential yields of the selected crops. The results overall illustrate the applicability of a comprehensive hydrological modelling system for the management of water resources for agricultural purposes in a watershed. # 1999 Elsevier Science B.V. All rights reserved. Keywords: Crop yield; Irrigation planning; Simulation; Water balance; Watershed modelling
1. Introduction Management of land and water resources for enhancing the agricultural production is of growing concern worldwide and this is especially true for developing countries like India. Since by 2000 AD India needs to meet the growing demand of food, fodder and * Corresponding author. Tel.: +91-3222-55224; fax: +91-3222-55303; e-mail: [email protected] 0378-3774/99/$ ± see front matter # 1999 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 2 2 - 0
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fuel for an expected population of 1000 million with diminishing per capita land availability (from 0.50 ha in 1983 to 0.33 ha in 2000 AD), the Ministry of Agriculture, Government of India has set the guideline that watershed is the most rational unit for planning and implementation of the programmes dealing with agricultural production. Subsequently, watershed management has become the cornerstone of planning and development of land and water resources in the country. The major objective behind the watershed approach is to enhance agriculture production in rainfed areas through efficient use of natural resources, within the natural boundaries of the development area. Hydrological simulation models form the basis of information for decisions regarding the development and management of water and land resources in a watershed. Though many hydrological models have been developed in the past, these are mostly lumped, i.e., they refer to the spatially averaged condition of the entire basin (Crawford and Linsey, 1963; Sittner et al., 1969; Holtan et al., 1975; Sugawara et al., 1984). Furthermore, their parameters have no direct physical meaning and cannot easily be derived from measurable properties of the basin. Thus, their applicability is limited only to gauged watersheds where no significant changes in catchment conditions have occurred. To overcome these limitations, considerable efforts within hydrological research have been directed towards development of distributed physically based catchment models (Beven et al., 1984; Rogers et al., 1985). Such models use parameters related directly to the physical characteristics of the catchment viz. topography, soil, vegetation and geology; and spatial variability in both physical characteristic and meteorological conditions. MIKE SHE (Refsgaard and Storm, 1995), a major development in this direction, is a comprehensive deterministic, distributed and physically based modelling system capable of simulating all major hydrological processes in the land phase of the hydrological cycle. Though it has been widely adopted for catchment studies (Bathurst, 1986a, b; Refsgaard et al., 1992; Jain et al., 1992), its applicability for irrigation planning has remained limited (Lohani et al., 1993; Singh et al., 1997). In the present study (Subramanian, 1997), MIKE SHE is adopted for the hydrological modelling of a small watershed with special emphasis on irrigation planning and the methodology and results are presented here. 2. Methodology 2.1. Description of MIKE SHE MIKE SHE is a distributed physically based modelling system capable of describing the entire land phase of the hydrological cycle over the model area. The model area is discretized by two analogous horizontal-grid square networks for surface and ground water flow components. A vertical column of nodes at each grid representing the unsaturated zone (Fig. 1) links these. A finite difference solution of the partial differential equations, describing the processes of overland and channel flow, unsaturated and saturated flow, interception and evapotranspiration, is used for water movement modelling. Though MIKE SHE is well-documented (Abbott et al., 1986a, b; Refsgaard and Storm, 1995), a brief description of its components is given in the following.
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151
Fig. 1. Schematic representation of MIKE SHE model structure.
2.1.1. Interception and evapotranspiration component The interception process is modelled by introducing an interception storage, expressed as a function of leaf area index (Jensen, 1983). The actual evapotranspiration is calculated based on the potential evapotranspiration using the Kristensen and Jensen model (Kristensen and Jensen, 1975). The actual evapotranspiration rate, consisting of the sum of actual transpiration and soil evaporation, is further adjusted according to vegetation density and water content in the root zone. Actual transpiration depends on the density of crop green material, described by the leaf area index, LAI, soil moisture content in the root zone and the root density. It is expressed as follows. Eat f1 LAIf2 RDFEp
(1)
where Eat actual transpiration; f1 LAI leaf area index function (Fig. 2(a)); f2 soil moisture function (Fig. 2(b)); RDF root distribution function; and Ep potential evapotranspiration. The soil moisture function, f2 , is mathematically expressed as follows: f ÿ c3 Ep (2) f2 1 ÿ f ÿ w where f volumetric moisture content at field capacity; w volumetric moisture content at wilting point; volumetric moisture content; and c3 empirical parameter, mm/d.
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Fig. 2. Variation of f1(LAI) with leaf area index and parameters c1 and c2, (b) Variation of f2() with potential evapotranspiration for constant c3, (c) Variation of soil evaporation with the soil moisture content in upper layers.
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The soil evaporation takes place only from the upper layers (top four nodes in the model set up) and consists of basic evaporation, Ep f3 , and evaporation from the possible water reserve in the upper layers. It is expressed as follows: Es Ep f3 Ep ÿ Eat ÿ Ep f3 f4 1 ÿ f1 LAI
(3)
where Es soil evaporation; and functions f3 and f4 are expressed as follows: 8 for w ; <0 (4) f3 c2 =w for r w ; : for w ; c2 where r residual soil moisture content; and c2 empirical parameter. 8 < ÿ 0:5 w f for 0:5 w f ; f4 f ÿ 0:5 w f : 0 else
(5)
Fig. 2(c) illustrates the variation of soil evaporation, i.e., Es/Ep, with the soil moisture content in the upper layers. The typical values of empirical parameters c1, c2 and c3 for agricultural crops are recommended as 0.31, 0.15 and 10 mm/d respectively. As evident from the governing equations, leaf area index and root depth need to be specified as a function of time for the actual evapotranspiration calculations. 2.1.2. Overland and channel flow component The overland flow process is simulated in each grid square by solving the twodimensional diffusive wave approximation of the Saint±Venant equations. For stream network channel flow, the one-dimensional form of the equation is solved in a separate node system located along boundaries of the grid squares. 2.1.3. Unsaturated zone component Soil moisture distribution in the unsaturated zone is calculated by solving the onedimensional Richards' equation. Extraction of moisture for transpiration and soil evaporation is introduced via sink terms at the node points in the root zone. Infiltration rates are found by the upper boundary that may be either flux controlled or head controlled. The lowest node point included in the finite difference scheme depends on the phreatic surface level, and allowance is made for the unsaturated zone to disappear in cases where the phreatic surface rises to the ground surface. 2.1.4. Saturated zone component The ground water flow is modelled using an implicit finite difference solution of the two-dimensional non-linear Boussinesq equation for an unconfined aquifer. The interaction between the streamflow and groundwater system is calculated on the basis of water levels in the river system and the groundwater table. 2.2. Study area and data availability The watershed under study is located in the western part of the Midnapore district of West Bengal, India between 208200 and 228230 N latitude and 87890 and 878110 E
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Fig. 3. Topographic map of the watershed.
longitude, and forms a part of the 66-B catchment of the Kangsabati river. The geographical area of the watershed is 694 ha. The climate is tropical sub-humid, with average annual rainfall of 1400 mm, 90% of which occurs during the Southwest monsoon (Jun±Oct). The area is primarily rainfed, though a small tank of 170 000 m3 capacity exists for supplemental irrigation. Paddy is the main crop grown in the area. Data on various aspects of the watershed viz. topography, geology, soils, crops, groundwater and meteorology are obtained from the Soil Conservation Department, Government of West Bengal and processed. Fig. 3 presents the topographic map of the area. As evident, the area is slightly undulating with elevation difference of about 30 m between the highest point on the ridge and the outlet. It is also seen that the elevation is decreasing towards the centre of the watershed from both sides of the boundary, along the length of the watershed. This directs the runoff water towards the centre of the watershed first and then to the outlet. Fig. 4 shows the land use patterns of the area. The central part of the area is cultivated land where the elevations are comparatively less. There are a few patches of fallow land. The major proportion of the watershed is under forest. Fig. 5 shows the soil type distribution map of the watershed. There are eight types of soil present in the area, ranging from slow to rapid draining. However, medium draining soils cover most of the cultivated area. Table 1 presents the experimentally determined pertinent physical characteristics of the soils in the area. Fig. 6 shows the stream network having a 4th order main stream. The main stream discharges into a storage tank constructed at the outlet. The water stored in the storage tank is pumped and used for the supplemental irrigation through a network of field channels. To model the inflow into the storage tank, a point neat the outlet is selected for storing the stream flow data during the simulation.
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Fig. 4. Land use pattern map of the watershed.
The major crops are paddy during kharif season (Jul±Oct) and wheat, gram and mustard during the rabi season (Nov±Feb). The crop characteristics like potential yield, leaf area index and root depth are obtained from government experimental farm.
Fig. 5. Soil distribution map of the watershed.
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Table 1 Pertinent physical properties of soils Drainability
Soil name
Bulk density (g/cc)
Saturated hydraulic conductivity (m/s)
Slow
Rg5A1 IIs-top Rg5A1 IIs-bot Hc5A1 IIs-top Fe5A1 IIs Mc5A1 IIs Hc5A1 IIs-bot Mb5B1 IIs Sb1B3 VIIs Sb3B2 IIIs Sb1B3 VIIIs
1.62 1.55 1.60 1.58 1.53 1.65 1.48 1.36 1.50 1.61
3.23 10ÿ7 8.90 10ÿ7 2.03 10ÿ7 1.30 10ÿ7 1.53 10ÿ6 2.98 10ÿ6 3.10 10ÿ6 2.14 10ÿ6 8.90 10ÿ6 1.07 10ÿ5
Medium
Rapid
2.3. Model simulations For running the simulation a grid size of 50 m 50 m is used with automatic classification. Daily simulations are first carried out for the main cropping season, i.e., kharif, over 109 days (Jul 7±Oct 21, 1993). The results are analysed and after assessing the availability of water for the subsequent dry rabi season, the simulations are further extended over 101 days (Nov 4, 1993±Feb, 12, 1994). 3. Results and discussion 3.1. Kharif season 3.1.1. Water balance of the watershed Table 2 presents the weekly-accumulated average water balance of the watershed. It gives the water flow and storage and also the water balance error in the calculation. The total accumulated precipitation during the simulation period is 1334 mm, the daily distribution of which is presented along with the pan evaporation in Fig. 7. The accumulated actual evapotranspiration, including the soil evaporation, is 1184 mm of water, whereas the deficit in the unsaturated zone varies from ÿ295 to ÿ441 mm (a change of ÿ246 mm). The accumulated average value of water stored on the ground surface is 39 mm. An accumulated water balance error of ÿ45 mm (around 4% of the accumulated precipitation) is also observed. 3.1.2. Infiltration to the paddy fields The accumulated infiltration to the paddy field is 628 mm for the greater proportion of the area. However, it is slightly less for the slow draining soil at the downstream side of the watershed. Fig. 8 shows the variation of infiltration to the paddy fields. At the beginning of the season the infiltration rate is comparatively high due to frequent rainfall events.
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Fig. 6. Stream network in the watershed.
3.1.3. Water content at each node of the soil column Fig. 9 shows the water content at each node of the soil column. In spite of the frequent rainfall there are phases when the moisture content in the root zone falls below the allowable deficit (field capacity in case of paddy). This shows that irrigation is needed to meet the crop water demand and to help crop attain its potential yield.
Table 2 Weekly-average accumulated water balance for the kharif season yy-mm-dda 93-7-7 93-7-14 93-7-21 93-7-28 93-8-4 93-8-11 93-8-18 93-8-25 93-9-1 93-9-8 93-9-15 93-9-22 93-9-29 93-10-6 93-10-13 93-10-20 93-10-21
ac.p.b 0 36 137 238 282 282 687 758 820 927 1142 1160 1263 1315 1317 1333 1334
ac.ep.c 0 40 147 251 279 279 627 728 784 805 1071 1092 1113 1137 1160 1181 1184
h-ovld 13 21 29 34 36 36 37 38 38 38 38 38 39 38 39 39 39
q-rive 0 12 23 32 43 43 65 75 86 97 107 119 129 140 151 162 164
thuzf
qszbg
qocbh
ÿ295 ÿ329 ÿ362 ÿ389 ÿ392 ÿ392 ÿ370 ÿ417 ÿ430 ÿ360 ÿ430 ÿ449 ÿ385 ÿ375 ÿ415 ÿ437 ÿ441
0 5 9 12 15 15 19 21 24 26 28 31 33 35 38 41 42
0 1 3 4 5 5 7 8 9 10 11 13 14 16 18 20 20
a
Output year, month and day. Accumulated precipitation. c Accumulated actual evapotranspiration. d Water stored on the ground surface. e Accumulated river outflow. f Deficit in the unsaturated zone. g Net outflow from the top layer of the saturated zone. h Net outflow from overland flow across the catchment boundaries. i Water balance error. b
Fig. 7. Rainfall and evaporation data.
wbleri 0 ÿ3 ÿ6 ÿ11 ÿ14 ÿ14 ÿ20 ÿ24 ÿ26 ÿ29 ÿ34 ÿ34 ÿ38 ÿ42 ÿ43 ÿ45 ÿ45
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159
Fig. 8. Infiltration to the paddy fields.
3.1.4. Calibration of the model The model is calibrated in three stages. Firstly, by matching the hydraulic conductivitymoisture content relationships derived by the MIKE SHE, based on the soil moisture retention characteristics, saturated hydraulic conductivity, residual moisture content and exponent, and the experimentally determined k± relationships. This is because the previous experience (Singh et al., 1997) has shown the sensitivity of the modelling system to the soil properties. Secondly, the pre- and post-monsoon groundwater table levels, actual and model derived, are matched over the watershed. Here, to match the premonsoon water table level, a separate simulation is run over 36 days (Jun 1±Jul 6). Once
Fig. 9. Water content of an upstream node during kharif season.
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Fig. 10. Comparison of measured and simulated stream flow data.
the desired water table is attained the output file of this simulation is used to provide the initial conditions for the main simulation (hot-start in MIKE SHE terminology). This simulation also helps in calibrating the hydrological properties of the subsurface strata, i.e., horizontal and vertical hydraulic conductivity, specific yield and storage coefficient. Lastly, the simulated daily stream flow is compared with the measured stream flow at the outlet of the watershed for a period of 21 days (Aug 11±Aug 31). Fig. 10 presents the plot of simulated and measured flow over the period. The visual comparison shows that the model performs satisfactorily. However, to evaluate the model performance statistically, two goodness-of-fit criteria, recommended by the ASCE Task Committee (The ASCE Task Committee on Definition of Criteria for Evaluation of Watershed Models, 1993) for evaluating the watershed models, are used. These are the deviation of the flow volumes, Dv, and Nash±Sutcliffe coefficient, R2, and are described below. The first criterion, Dv, complements the visual inspection of the continuous flow record and should be small for model to be acceptable (Dv equals zero for a perfect model). It is mathematically expressed as Dv %
V ÿ V0 100 V
(6)
where V measured flow volume; and V 0 simulated flow volume. The second criterion, R2, is a measure of how well the daily simulated and measured flows correspond and can vary from 0 to 1 (1 indicating a perfect fit). It is mathematically expressed as Pn Qi ÿ Q0i 2 2 (7) R 1 ÿ Pi1 n 2 i1 Qi ÿ Q where Qi measured daily discharge; Qi0 simulated daily discharge; Q average measured discharge; and n number of daily discharge values.
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The values of Dv and R2 for the data set presented in Fig. 10 are found to be 5.7% and 0.68 respectively. This shows that the model performance is satisfactory for the watershed. In addition to these criteria, Student's t-test is also applied to test the difference of means of measured and simulated data. The means of the measured and simulated data are 0.232 and 0.219 m3/s with standard deviations of 0.082 and 0.073 respectively. The calculated value of variable T is 0.53, which is well within the table value, i.e., 2.70, at 1% level of significance. Hence, there is no significant difference between the means of measured and simulated data. This further enforces the conclusion that the model performance is acceptable for the watershed. 3.1.5. Evaluation of the paddy yield The actual yield of the paddy is calculated from the FAO relationship (Doorenbos and Kassam, 1979), modified by replacing evapotranspiration terms with transpiration. The modified relationship is as follows. X n Ya Eat i Ky 1 ÿ (8) 1ÿ Ym Emt i1 where, Ya, Ym actual and maximum attainable yields; Eat actual transpiration; Emt maximum transpiration that would have occurred if there had been no water stress; Ky yield response factor; and i crop growth stage. Eq. (8) performs better than the original FAO relationship when used with the Kristensen and Jensen model (Jorgensen, 1995). Eat and Emt in Eq. (8) are estimated by deducting the soil evaporation from the actual and maximum evapotranspiration values, where the soil evaporation and actual evapotranspiration are estimated using Kristensen and Jensen model. The yield response factor, Ky, is determined from literature (Doorenbos and Kassam, 1979). Using Eq. (8), the actual paddy yield is estimated for periods where soil moisture deficit occurs. It is found that in case irrigation is not supplied the paddy yield will be around 70% of the maximum attainable yield. This shows that the prospects of increasing yield by providing irrigation are high. 3.1.6. Irrigation water requirement of the area To avoid reduction in the paddy yield, the irrigation water requirements (to bring the soil moisture content to the field capacity during the dry phases) are calculated and found to be comparatively higher for the upstream side of the watershed. The total irrigation requirements are 490 and 340 mm for the upstream and downstream sides of the watershed respectively. Fig. 11 presents the amount of water required and the suggested days of applications for the upstream end of the watershed. 3.1.7. Tank storage The water available for storage in the tank is calculated by deducting the total irrigation requirement from the total inflow to the tank for the corresponding month. During July to October, this is found as ÿ48 000, 118 900, 927 000, 233 400 m3 respectively. The negative sign indicates that the monthly irrigation requirement in July exceeds the monthly river inflow. However, this deficit can be met with the existing storage (before simulation) in the tank. The net inflow to the tank at the end of simulation period is
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Fig. 11. Irrigation water requirement for paddy.
estimated as 445 000 m3 though the existing tank capacity is 170 000 m3 only. This shows that the tank capacity can be increased further. This also shows that at the end of the kharif season 170 000 m3 of water remains available for meeting the irrigation water requirement of crops in the subsequent dry rabi season. 3.2. Rabi season 3.2.1. Irrigation for rabi crops The 170 000 m3 of water stored in the outlet tank is considered for irrigating the rabi crops, i.e., wheat, mustard and gram. Consequently, the depth of water available for irrigation is calculated as 54 mm, assuming an overall irrigation efficiency of 70% (Interim Report, 1982). Since the available water is not sufficient to meet the crop water demand, protective irrigation is provided during the critical crop growth periods. Fig. 12 presents the amount and distribution of the protective irrigation for the selected crops. Further, to reduce the computation requirements, field channels are not included in the model setup. The irrigation amount, instead, is modelled as the rainfall.
Fig. 12. Amount and distribution of irrigation water for rabi crops.
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163
Table 3 Weekly-average accumulated water balance for rabi season yy-mm-dda
ac.pb
93-11-4 93-11-11 93-11-18 93-11-25 93-12-2 93-12-9 93-12-16 93-12-23 93-12-30 94-1-6 94-1-13 94-1-20 94-1-27 94-2-3 94-2-10 94-2-12
0 3 3 3 3 6 10 11 12 14 18 35 82 82 82 82
ac.ep.c 0 14 28 44 59 73 86 98 111 124 136 147 165 181 192 195
h-ovld
q-rive
1 3 5 7 9 11 13 15 17 18 20 21 23 25 26 27
0 4 7 11 14 16 19 21 23 25 27 29 31 33 34 35
thuz6 ÿ468 ÿ486 ÿ507 ÿ530 ÿ551 ÿ568 ÿ584 ÿ600 ÿ617 ÿ633 ÿ645 ÿ644 ÿ619 ÿ639 ÿ654 ÿ659
qszb7
qocb8
wbler9
0 1 1 2 3 4 4 5 6 6 7 7 8 9 9 10
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 ÿ1 ÿ1 ÿ2 ÿ3 ÿ3 ÿ4 ÿ4 ÿ5 ÿ6 ÿ5 ÿ6 ÿ6 ÿ7 ÿ7 ÿ7
a
Output year, month and day. Accumulated precipitation. c Accumulated actual evapotranspiration. d Water stored on the ground surface. e Accumulated river outflow. f Deficit in the unsaturated zone. g Net outflow from the top layer of the saturated zone. h Net outflow from overland flow across the catchment boundaries. i Water balance error. b
3.2.2. Water balance of the watershed Table 3 shows the average weekly water balance of the watershed for the rabi season. Here, the actual evapotranspiration is 195 mm against the total precipitation of 82 mm which includes actual rainfall and total irrigation simulated as rainfall. Also, the deficit in the unsaturated zone varies from ÿ468 to ÿ654 mm (a change of ÿ186 mm). This shows that the soil water stored in the root zone mostly meets the crop water demand. The result here is in tune with the existing conditions in the field where the rabi crops are grown with bare minimum irrigation. 3.2.3. Water content at each node of soil column Fig. 13 shows the representative soil moisture distribution pattern in the root zone for different crops. It is seen that in all cases the moisture content remains well within the readily available moisture content limit during the entire cropping period. For this analysis, a maximum allowable depletion (MAD) value of 0.5 is considered (Stegman, 1983). This shows that the supplemental irrigation provided during critical periods of the crops helps in maintaining the soil moisture status within the desirable limit, in spite of negligible rainfall during the season.
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Fig. 13. Water content for representative nodes during rabi season.
3.2.4. Yield evaluation Using the modified FAO relationship in Eq. (1), the actual yields for the three crops are calculated. It is found that the actual yields are very close to the maximum attainable yields. This shows the importance of supplemental irrigation in the rabi season. Here, it may be noted that the modelling system offers a flexibility to users to change the irrigation schedule in this season, if the actual yield calculations are not favourable. However, since the actual yield values are favourable, the same is not attempted here. 4. Discussion MIKE SHE, a comprehensive physically based distributed modelling system is adopted here for irrigation planning of a small watershed. The modelling system though provides
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the users with a chance to utilise large amount of parametric and input data, its application is not necessarily restricted due to unavailability of some of the data. This is because the model set up can be simplified according to the users' conceptualization of the natural system and the data availability. MIKE SHE, therefore, provides greater flexibility as compared to many simpler models when describing a natural system (Refsgaard and Storm, 1995). Concerning irrigation, MIKE SHE is primarily proposed here as a planning tool and not as a real-time scheduling tool. The major problem faced in rainfed agriculture is the unavailability of irrigation water for the non-rainy cropping season (rabi). This is either due to lack of facilities to store excess water in the rainy season or due to poor management of stored water, over-irrigation in the kharif season often being the culprit. The watershed under study falls in the later category. The application of MIKE SHE in carrying out the detailed hydrological water balance study plays an important role in evaluating the irrigation demands in the kharif season and in deciding the magnitude of water that can be stored for irrigation in the subsequent dry season. This consequently facilitates irrigation and encourages the farmers to cultivate the second crop that is often ignored otherwise. It may, however, be noticed that the advantages of the modelling system cannot be quantified in terms of total production or yield. This is because the crop yield depends on several inputs whereas the analysis here involves only the water production function. Nevertheless, from a qualitative assessment the results appear to provide a reasonable representation of the field conditions in the watershed. 5. Conclusions The hydrological water balance of a small rainfed watershed is simulated using MIKE SHE. Simulation results show that in spite of frequent rainfall during the kharif season, supplemental irrigation is essential for paddy to obtain the potential yield. Based on the water balance analysis, an irrigation schedule for paddy is suggested. Further, the inflow to the outlet tank is analysed and the irrigation water available for the subsequent dry cropping season is estimated. An irrigation plan is then suggested for protective irrigation during the season. Simulation results for the season show that with the proper planning it is possible to meet the irrigation demand of the crops. The study, thus, illustrates the applicability of the comprehensive hydrological modelling system for planning and analysing the irrigation water requirements of crops, based on water balance analyses. Acknowledgements This research was funded by the Indian Council of Agricultural Research, Government of India through a sponsored project. The assistance of Mr. I. Banerjee, B.Tech. student at I.I.T., Kharagpur, in detailed calibration of the model is duly acknowledged. The help rendered by the Watershed officials in data collection is also acknowledged. The authors are grateful to the two referees for their thoughtful criticism and suggestions.
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